Quantifying the Impact of Services Liberalization in a Developing Country
Denise Eby Konan
Department of Economics, University of Hawaii, Honolulu, HI 96822
Phone 808-956-5971 Fax 808-956-7115 Email konan@hawaii.edu
Keith E. Maskus
Department of Economics, Box 256, University of Colorado, Boulder, CO 80309
Phone 303-492-7588 Fax 303-492-8960 email maskus@colorado.edu
and
World Bank, 1818 H Street NW, Washington, DC 20433
Phone 202-473-4460 Fax 202-522-1159 Email kmaskus@worldbank.org
JEL Classification: C68, F13, F14, F23, L8
Keywords: Liberalization, Services, Regulation, Computational Economics, Tunisia
World Bank Policy Research Working Paper 3193, January 2004
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the
exchange of ideas about development issues. An objective of the series is to get the findings out quickly,
even if the presentations are less than fully polished. The papers carry the names of the authors and should
be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely
those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors,
or the countries they represent. Policy Research Working Papers are available online at
http://econ.worldbank.org.
We gratefully acknowledge Sherry Stephenson, Bernard Hoekman, Mohamed Goaied,
and Dominique van der Mensbrugghe for valuable discussions throughout the writing of
this paper, and Aristomene Varoudakis for his comments. We also thank Robert Lipsey,
Asim Erdilek, and other participants at the 2001 Western Economics Association annual
conference for constructive comments.
ABSTRACT
The authors consider how service liberalization differs from that of goods liberalization
in terms of welfare, the levels and composition of output, and factor prices within a
developing economy, in this case Tunisia. Despite recent movements toward
liberalization, Tunisian service sectors remain largely closed to foreign participation and
are provided at high cost relative to many developing nations. The authors develop a
CGE model of the Tunisian economy with multiple products and services and three
trading partners. They model goods liberalization as the unilateral removal of product
tariffs. Restraints on services trade involve both restrictions on cross-border supply
(mode 1 in the GATS) and on foreign ownership through foreign direct investment (mode
3 in the GATS). The former are modeled as tariff-equivalent price wedges while the
latter are comprised of both monopoly-rent distortions (arising from imperfect
competition among domestic producers) and inefficiency costs (arising from a failure of
domestic service providers to adopt least-cost practices).
They find that goods-trade liberalization yields a modes gain in aggregate welfare and
reorients production toward sectors of benchmark comparative advantage. However, a
reduction of services barriers in a way that permits greater competition through foreign
direct investment generates large welfare gains. As a result, service liberalization
requires lower adjustment costs, measured in terms of sectoral movement of workers,
than does goods-trade liberalization. Moreover, it tends to increase economic activity in
all sectors and raise the real returns to both capital and labor. Overall welfare gains of
comprehensive service liberalization amount to over five percent of initial consumption.
The bulk of these gains come from opening markets for finance, business services, and
telecommunications. Because these are key inputs into all sectors of the economy, their
liberalization cuts costs and drives larger efficiency gains overall. The results point to the
potential importance of deregulating services provision for economic development.
1
1. Introduction
The dramatic economic growth that visited much of the world in the 1990s has been
attributed often to a `new economy' arising from global integration. Yet, the economies of many
developing countries in Africa and Latin America experienced slower growth or remained
stagnant. This history is puzzling as there has been an unprecedented willingness on the part of
many developing economies to participate in the globalization of merchandise trade. Through
both unilateral trade liberalization and agreements reached in the World Trade Organization and
regional trade accords, many countries sharply lowered manufacturing tariffs and other
impediments to goods trade. Nevertheless, as Rodrik (2001) has pointed out, traditional trade
liberalization seems not to have fully delivered on its promise for prosperity. In this paper we
suggest that part of the explanation for this weak performance rests in the continued insulation,
and resulting poor condition, of the domestic services sectors in many developing countries.
These service sectors tend to deliver high-cost and unproductive input services to export
industries, thereby limiting economic efficiency gains from trade reform. We explore this claim
in a computational general equilibrium model of the Tunisian economy.
The mechanisms by which services trade liberalization might improve welfare differ
from those of goods trade. As is well known, producers respond to a lowering of border barriers
in products by reorienting production towards goods in which an economy possesses a
comparative advantage. Goods trade thus involves a restructuring of the economy as labor and
capital move out of import-competing sectors and into export sectors. Goods trade also tends to
redistribute income, with abundant factors benefiting disproportionately from liberalization in the
long run.
In contrast, trade in services is not solely a cross-border phenomenon. As the paper by
Markusen, Rutherford and Tarr (1999) points out, many foreign services are best transferred
through foreign direct investment (FDI) due to the personal contact that is often required between
2
the service provider and client. Restrictions on FDI or the movement of professional personnel
may reduce services trade far more than tariffs or other border barriers limit trade in goods.
Indeed, in many developing countries, Tunisia included, laws and regulatory agencies erect entry
barriers that essentially rule out FDI in key service sectors.
Foreign direct investment involves inflows of capital and personnel, but more importantly
for developing countries it also tends to embody transfers of technology that can upgrade
productivity in the domestic economy. Because financial, communications, and professional
services are key intermediate inputs into production in all sectors, technological improvements in
these sectors could have the effect of upgrading overall productivity. Thus, whereas liberalizing
goods trade moves an economy toward specialization, liberalizing services trade through
permitting foreign establishments could lead to more balanced output expansion.
In industrialized countries certain producer services are among the largest and most
dynamic components of production and employment. For example, technological innovations in
information management and telecommunications services have facilitated the global transactions
upon which the "new economy" has thrived (Lipsey, 2001).
This situation lies in stark contrast with Tunisia, where there is a large state presence in
many key service sectors. Regulatory agencies limit competition by restricting markets available
to producers. Foreign participation is also highly restricted and often limited to the services of
non-resident Tunisian suppliers. As we discuss below, anecdotal evidence indicates that
Tunisia's communication, financial, insurance, distribution, and professional services are
expensive, of poor quality, and often inaccessible. An inefficient service sector acts as a drag on
the entire economy, and especially on trade, as services are critical inputs in production and
distribution processes.
In some respects, Tunisia has pursued a strategy of liberalization and alignment with the
global economy. However, Tunisia's 1995 commitments under the General Agreement on Trade
3
in Services (GATS) are few and generally represent a preservation of status quo policies.1 The
opening of services markets to foreign suppliers would also involve privatization and
deregulation. Policymakers are concerned about whether the economic benefits would justify the
adjustment costs involved. Moreover, Tunisian services are supplied by important domestic
interests, which makes liberalization difficult to undertake without some indication of the
potential for gains and information on their likely distribution.
Unfortunately, there are very few empirical studies on services trade and FDI, in part due
to a variety of measurement problems. It is against this backdrop that the present study is
conducted. We employ a computable general equilibrium (CGE) model to compare the impact of
service liberalization to that of trade liberalization. We follow GATS definitions and consider,
separately, liberalization of both cross-border services trade (mode 1) and the establishment of
domestic presence by foreign direct investment (mode 3). For this purpose we develop estimates
of the distortions that the present, relatively closed, environment in Tunisia imposes on the price
of services. By simulating the effects of removing these distortions, we are able to quantify the
impacts of liberalization. The potential efficiency gains would be large, while output in all
merchandise sectors would rise, after services liberalization. Furthermore, the real prices of both
capital and labor would increase.
2. Conceptual Issues
Trade in services is distinguished from trade in goods by the intangible nature of many
transactions. Unlike physical goods, which must cross borders and thus are subject to customs
procedures and tariffs, services often involve direct transactions between the consumer and
producer. This complicates the measurement of both service flows and their corresponding
impediments. The founders of the GATS framework recognized the importance of the various
channels by which services are transacted. GATS identifies four modes of supply: cross-border
1Of the twelve service sectors defined under the GATS classification scheme Tunisia made commitments
4
supply (mode 1), consumption abroad (mode 2), commercial presence (mode 3), and the presence
of natural persons (mode 4). Thus GATS extends traditional trade law to include both foreign
direct investment (mode 3) and movements of labor (mode 4).
Unfortunately, these legal definitions do not accord well with present international
balance of payments accounting practices, as discussed in detail by Karsenty (2000), making
difficult the measurement of services trade and its components. Equally problematic is the
measurement of impediments to services trade. Warren and Findlay (2000) and Hoekman (2000)
provide excellent surveys of these measurement issues. For example, Hoekman (1995) developed
a frequency indicator as an initial attempt to quantify the presence of barriers based on the GATS
schedule of commitments by country. While this provides some indication of the extent of
commitments, the index is not designed to measure the level of barriers present. Francois (1999)
estimates a gravity model of services trade, adopting Singapore and Hong Kong as free-trade
benchmarks. In his approach, discrepancies in predicted trade patterns are used to indicate the
severity of policy barriers. Warren and Findlay (2000) describe an ongoing Australian services
research project that is attempting to measure the wedge between price and marginal cost in
service sectors in order to get an indication of the impact that impediments might have on prices.
The project also seeks to develop quantity impact measures by comparing domestic output to
international standards. Unfortunately, the study is incomplete and ultimately may not provide
information that could be applied to developing economies.
Given severe data limitations, there are very few econometric studies on services trade
and their barriers. One advantage of a CGE model is that it can provide quantifiable insights with
relatively sparse datasets. Several studies of services barriers exist using the GTAP multi-country
database.2 An early model by Brown, et al (1996) converts Hoekman's frequency indices into an
approximation of cross-border barriers to services trade and simulates liberalization in the multi-
in only three: financial services, tourism, and telecommunications. These commitments reflect little more
than a codification of Tunisia's present legal system.
5
country Michigan model. Hertel (2000) approximates cross-border barriers with the gravity-
equation estimates of Francois and treats liberalization as an elimination of resource-using
barriers. A significant limitation of these models is that they do not capture the potential benefit
of FDI liberalization.
More recently, FDI has been incorporated into multi-country GTAP-based models (Dee
and Hanslow, 2001; Brown and Stern, 2001). FDI is treated as a capital flow and barriers to the
right of establishment are modeled as taxes on the existing investment flow and on local sales.
Liberalization (removal of the tax) results in a global reallocation of capital as sector-level rates
of return adjust to a new equilibrium. This approach represents a significant improvement over
earlier work, which focused only on cross-border trade (Mode 1).
Nonetheless, although these models inform our understanding of global impacts of
GATS, they are not adequate for understanding domestic impacts in such highly regulated
developing economies as Tunisia for two reasons. First, service sectors that experience no FDI in
the benchmark economy are assumed to be non-tradable and could not, therefore, be recipients of
FDI in counterfactual scenarios. Yet in Tunisia, we might reasonably expect that FDI would
occur in several important sectors (such as telecommunications or insurance) in which, under
current policy, foreign suppliers are simply not permitted to serve Tunisian residents. Existing
methodologies do not offer a reasonable way to predict how responsive sectors that are inactive in
the benchmark would be to FDI in a liberalized environment. Second, the market structure in
most service sectors in Tunisia is highly regulated and imperfectly competitive, perhaps best
characterized as cartels. As Francois and Wooten (2001) discuss, shallow liberalization without
deregulation could involve essentially an invitation to foreign firms to join the cartel. Deeper
liberalization, involving also deregulation permitting new entry, should bring about a more
competitive market structure than envisioned in earlier models.
2See Dee, et al (2000) for an excellent survey of this literature.
6
An additional point of departure for our work is to consider the impact of services
liberalization on the structure of Tunisia's economy relative to that of trade liberalization. The
Tunisia input-output table allows us to disaggregate services into 15 sectors. We consider the
regulatory environment at a disaggregated level and are able to compare the relative impact of
liberalization in individual service sectors. With data on the manner in which services act as
intermediate inputs, our simulations are indicative of how service liberalization may restructure
the domestic economy.
3. The Model and Benchmark Data
Services play a significant role in the Tunisian economy, as is evident from Table 1.
Nearly half of all output (excluding tourism) is comprised of services. Output of commercial
services has been growing at a faster rate than that of goods. Services make up one-third of
household consumption and eighteen percent of intermediate demand according to the 1995
input-output table (Institute National de la Statistique, 1998). Of the tradable services, tourism
plays the most significant role, representing over fifteen percent of imports and more than 19
percent of all exports. Tourism export services are considered to be rather open.3
There is no statistical information on the importance of FDI in Tunisian services trade, as
the earnings and sales of foreign-owned subsidiaries are not reported separately from those of
domestic firms. However, foreign participation clearly is minimal in the main service activities in
Tunisia. This is due to a variety of investment measures, exchange controls and limits on
movement of foreign personnel. The most important restriction is the Foreign Commercial
Activities Law of 1961 (Decree Law Number 61-14), by which non-Tunisians are required to
obtain a trader's permit, carte de commercant, to engage in any form of commercial activity.
This permit, granted on a discretionary basis, has effectively precluded foreign participation in
most wholesale and retail markets. The Investment Code of 1993 is also an important barrier to
3Tourism may be exported without being produced because tourists are treated as "foreign consumers" in
7
majority foreign equity projects, with foreign entry requiring approval by regulatory councils.
Such approvals are rare and FDI is strictly controlled.
We employ what is, in most respects, a standard CGE model of a small open economy.
The full model is discussed below and presented in a technical appendix. Our contribution is in
the explicit treatment of services production and investment. Production decisions in the services
sector are distorted by regulations that raise entry costs and limit the rights of foreign enterprises
to establish facilities in Tunisia. In principle, this restriction distorts prices and quantities through
two primary channels. One is the cartel effect whereby barriers to FDI and excessive regulation
limit both domestic and foreign participants in certain service sectors, thus hampering
competition and supporting market power on behalf of local firms. This market power creates the
opportunity in sector i to charge price markups vi over marginal cost ci.
(1) ci (1 + vi) = pi
The markup depends on the number of firms, price elasticity of demand, and conjectures about
reactions of rival firms. We assume that the rents generated by markups accrue to the
representative agent.
Second is a cost inefficiency effect. Marginal costs in a regulated environment may be
excessively high as low-cost foreign suppliers are excluded from the market. Additionally,
domestic suppliers may be forced to absorb into their costs various regulations on provision and
bureaucratic procedures. These activities do not contribute to output and generate pure economic
waste (Hoekman and Konan 2001). Thus, resource-using service barriers i raise marginal costs
above `best practice' marginal costs ci that would prevail in a liberalized environment.
*
(2) ci (1 + i) = ci
*
the input-output table and enter as a component of final demand. The production of tourism services exists
in the other service sectors, such as transportation, hotels, and restaurants.
8
Combining equations (1) and (2) shows that the wedge between price and true marginal costs
depends on the product of an ad valorem markup and a proportionate waste factor. Ultimately it
would be preferable and interesting to locate empirical information on these two wedges in each
sector in order to simulate the effects of their separate and joint removal. Unfortunately, we only
have estimates of the entire price-cost wedge and cannot perform this decomposition except on
assumed shares. Thus, throughout the baseline counterfactual scenarios, it is assumed that
barriers to FDI generate wedges consisting of half rents and half waste.
Services liberalization involves presenting a domestic cartel the possibility of competitive
markets with foreign entry. It is important to note that liberalization does not, in our model,
generate endogenous changes in FDI flows. Rather, the scenarios involve changes in ownership
and market structure in ways that improve efficiency and alter the distribution of rents. This
assumption reflects the fact that in several service sectors there is no foreign participation (that is,
FDI) in the benchmark equilibrium. In that context it is impossible to determine what the impact
of liberalization would be on "marginal" FDI flows, which would not be meaningful. It also
permits us to retain a fixed aggregate capital stock in the model, rather than engaging in dynamic
simulations of endogenous investment and capital allocation. In this context, the estimates of
welfare changes from liberalization of establishment rules are likely to be understated relative to
full long-run gains.4
Model equations are presented in the appendix and the model is depicted in Figure 1. We
assume that production of agricultural, mineral, and manufacturing goods is characterized by
constant returns to scale and perfect competition, implying that prices equal marginal costs of
output.5 Services production is subject to constant returns as well, though in the initial
4Kehoe (2002) discusses the importance of incorporating changes in trade and investment flows in sectors
where they had been absent in the computation of new equilibrium outcomes. This observation stems from
the chronic tendency of CGE models of NAFTA to underpredict the ultimate impacts of that trade
agreement on Mexico's international trade and investment.
5This assumption is standard in the literature. See, for example, Konan and Maskus (2000).
9
benchmark it is monopolized as discussed above.6 In all sectors, production functions are
approximated with Leontief technologies using composite intermediate inputs and real value
added. A constant elasticity of substitution (CES) production function describes the
substitutability between labor and capital inputs in producing real value added. Intermediate
inputs and final goods are differentiated by country of origin according to the Armington
assumption, so that export and import prices differ across regions.7 The three trading regions are
the European Union (EU), the Arab League countries, and the rest of the world (ROW). In each
sector, demand for domestically produced and imported goods is represented by a CES function,
and intermediate imports are also differentiated across regional sources of supply in a CES
structure. Similarly, Tunisian industries supply regionally differentiated goods to both domestic
and foreign markets (exports). Production follows a nested two-stage constant elasticity of
transformation (CET) function. Total output is first calculated as the sum of domestic supply and
total exports, with the latter then being allocated across the same destination regions according to
a sub-CET function. Capital and labor are assumed to be freely mobile across sectors, implying
that our simulations pertain to long-run outcomes of liberalization.
A representative consumer maximizes a nested CES utility function with a corresponding
multi-staged budget constraint. In the first stage, the consumer decides how much to spend on
goods from each sector, given the budget constraint. Income elasticities across sectors are set at
unity as given by a Cobb-Douglas (CD) utility nest. In the second nest, the consumer determines
domestic and aggregate import expenditures in each sector according to a CES function. Then
given a budget for imports, the consumer selects purchases of imports from each region. These
latter functions also characterize the split between government consumption and investment
6 It is likely that a number of services, such as telecommunications, transport, and finance, are subject to
economies of scale and scope. Thus, our assumption of constant returns may understate the gains from
liberalization.
7 De Melo and Robinson (1989) show that models that allow product differentiation are well behaved
under a small open economy assumption; in effect the economy is a price taker at the level of aggregate
trade flows and each region's aggregation is sufficiently distinctive to support the Armington assumption.
10
spending on domestic and imported goods and services. The representative consumer receives
income from primary factors (labor and capital), net transfers from the government, the current-
account deficit, and any net economic rents from the operation of restrictions on services trade.
Two standard closure rules are imposed: the savings-investment balance and a fixed
current account balance. The savings-investment balance is based on the assumption that the
capital stock is exogenously fixed at the benchmark level. This stock is financed through forced
consumer savings that acts as a direct (lump-sum) tax. The interest rate (an index price of the
composite capital stock) is endogenous and determined by factor demand conditions. The
current-account is defined as the sum of the merchandise trade balance, the services balance, net
foreign worker remittances, and (negative) net payments on foreign capital.8 We assume that
foreign reserves will be held constant so that the current account will be just offset by (the
negative of) the capital account. The current-account balance itself is held constant in real terms
throughout the simulations. Income from foreign remittances less foreign capital payments enters
as an exogenous addition to the representative agent's income. To hold the current account
balance fixed while international prices are constant requires a balancing item. This is
accomplished by means of a change in the home "real exchange rate," which refers implicitly to a
change in the home price index (generated by changes in price of home-produced goods)
sufficient to sustain a constant current-account balance as import and export volumes change.
The government budget deficit is a deduction in available income for the representative
agent, constituting a transfer to government consumption. The deficit is held fixed during our
simulations. Thus, if a policy reform causes prices to fall, thereby reducing the tax revenues
required to finance government expenditures, this tax saving is transferred to the representative
agent. At the same time, if trade liberalization results in lost tariff revenues, the revenues are
recouped by means of allowing household lump-sum tax rates to vary endogenously.
8In the 1995 benchmark year, foreign remittances were approximately 650 million Dinars while net capital
11
The data for the model consist of a Social Accounting Matrix (SAM) and other
parameters, such as import and export trade flows by region, sectoral tax and tariff rates, and
elasticities of substitution and transformation. Because there is little empirical evidence on
relevant elasticities for the Tunisian market, we make standard assumptions about their values. In
particular, labor-capital substitution is set at unity in a Cobb Douglas value added production
function. Benchmark trade elasticities are drawn from Rutherford, Rutstrom and Tarr (1995) and
Konan and Maskus (2000). The various trade elasticities are 2.0 for substitution between domestic
and imported goods, 5.0 for substitution among regional imports and for transformation between
domestic output and exports, and 8.0 for transformation among regional export destinations. These
data are assembled into a consistent set of relationships between intermediate demand, final
demand, and value-added transactions using the 1995 input-output table for Tunisia on a diskette
provided by the Institut National De La Statistique (INS) along with the 1998 INS Les Comptes
de la Nation report.
Trade and tariff data, provided in Table 2, were aggregated to the input-output sectoral
basis using import weights consistent with the concordance between the input-output table and
the tariff classification. Tariff rates were determined by collections data for 1995 and vary across
regions due to duty drawback provisions as well as preferential treatment of the EU and the Arab
League. There are no data on tariff collections on services, and we take their tariff rates to be
zero.
Table 3 lists our estimate of price wedges due to service barriers, which are the key
parameters to be altered in the simulations. Mode 1 barriers on cross-border trade are treated as
ad valorem tariff-equivalent NTBs. These are simply set to zero in the liberalization exercises.
Sectors that are listed as non-traded (indicated by nt) remain non-traded post-liberalization. In
terms of mode 3, we would ideally like to estimate the impact that services barriers have on both
price markups and on resource costs so as to distinguish between the pro-competitive effects and
income totaled negative 680 million Dinars according to the IMF Balance of Payments Statistics Yearbook.
12
the cost-reduction effects. Warren and Findlay (2000) suggest computing the pro-competitive
impacts using price-cost margins (or "net interest margins"). Ideally, we would also like to
capture the cost-reduction effects by comparing actual costs to a constructed estimate of costs if
services were provided according to a `world's best-practice' cost function. Unfortunately, none
of these measurements are attainable for Tunisia, as is the case for most countries.
The services barriers given in Table 3 are based on industry studies in Tunisia and
extensive discussions with Tunisian industry experts, country economists and government
officials and on Zarrouk (2000). The financial services barriers estimates are taken from our
observation that the level of monetary intermediation in the banking system is about 30% lower
than in comparable countries (Bahlous and Nabli 2000) and on Goaied's (1999) estimation of the
cost inefficiencies in the financial sector. This is in line with the estimates of Kalirajan, et al
(2000) for the banking sectors in Chile, Singapore, South Korea, and Thailand. The price wedges
in insurance, communications, and transportation reflect the high level of benchmark regulation
in those sectors and comparisons with markets in similar countries (Vittas 1995, World Bank
2000). The distribution and retail sectors show large inefficiencies and are very fragmented,
making our 5% inefficiency measure conservative. Many professional services are subject to a
nationality requirement, thus restricting foreign participation, and it is possible that our 10%
estimated price wedge is low. While the construction, hotel, and restaurant sectors are viewed
here as already substantially liberalized and subject to a small price-cost wedge, foreign
participation remains subject to the investment code and projects are granted upon approval of a
Cahier des Charges. Remaining sectors (health and education, public services, and other
services) are taken to be exempt from potential liberalization.
13
4. Results
The liberalization scenarios considered can be broken down in several ways. First,
liberalization of investment barriers in services is considered. Sensitivity analysis demonstrates
the importance of the decomposition of the price wedge into resource-using versus rent-
generating barriers. The second step is to distinguish between liberalization of border barriers
and investment barriers, broadly. Next, the impacts of liberalization are broken down on a
sectoral basis. The final set of scenarios compares the impact of services liberalization to that of
traditional liberalization of trade in goods.
Table 4 presents potential impacts of lifting barriers to foreign investment in services
(mode 3 delivery). As discussed in the previous section, investment barriers are assumed to drive
an observable wedge between price and marginal cost. Unobserved is the decomposition of the
wedge into two sources of distortion: rent-generating (cartel effect) and resource-using
(inefficiency effect). Three benchmark possibilities are considered in Table 4. First (column
one), assume that the only barrier to foreign investment is one that preserves a domestic cartel
and thus generates pure economic rents for Tunisian interests. That is, Tunisian service producers
are using world-class technologies and face costs equivalent to those of the low-cost world
producer. Upon liberalization, foreign entry is assumed to eliminate the price-wedge as markets
become competitive. Domestic rents are completely dissipated to the benefit of Tunisian services
consumers. The result is a modest gain in welfare of the representative household of one-third of
one percent, measured as equivalent variation in the representative agent's real income.
At the other extreme (column three), assume services markets are perfectly competitive
in the benchmark, but that Tunisian firms do not employ world-class production techniques and
are thus inefficient. Entry by foreign firms introduces cost-saving innovations and services prices
fall. Welfare increases dramatically by nearly eight percent. This large difference from the initial
benchmark case reflects the fact that elimination of a pure rent wedge generates a small net gain
in efficiency from resource reallocation, but most of the gross gains are transfers from the prior
14
rent stream earned by the representative agent.9 In both cases consumer prices fall about seven
percent. Note that while both scenarios increase returns to both labor and capital (non-labor value
added), labor gains relatively more in the pure rent-wedge case. This suggests that one effect of
the protected cartel is to restrain wages in relation to what they would be under full efficiency.
Capital gains are relatively larger when the pure cost wedge is removed.
In the remainder of these counterfactual experiments, it is assumed that the price-wedge
is an equal combination of the rent-generating and resource-using distortions (column 2 of Table
4). Thus, in this case the welfare impacts mix efficiency gains with rent losses for the
representative agent. This baseline scenario for investment liberalization results in a four percent
increase in welfare and a seven percent fall in the consumer price index. The gains from
liberalization are skewed toward capital, the price of which increases seven percent. Five percent
of the capital stock changes sector of employment. Real returns to labor increase by three percent
and three percent of the labor force changes sector of employment.
The bottom part of Table 4 indicates impacts on major sectoral production shares. The
figures in parentheses in the left-most part indicate benchmark output shares before any
liberalization. Liberalization itself tends to favor relative output expansion in agriculture and
services, while restraining the manufacturing and mining shares. Thus, the initial structure of
protection for services actually restrains domestic output in that sector. The remaining columns
compare these shares across FDI-liberalization cases. While these shares are essentially stable
across benchmark assumptions, moving from the rent-wedge case to the efficiency-wedge case
slightly favors agriculture and manufacturing, while reducing the share of services.
Table 5 provides liberalization scenarios by mode of service delivery, assuming an equal
split of price markups between rents and costs in the benchmark. Assume that Tunisia eliminates
all border barriers (mode one barriers) on tradable services, and does so on a non-discriminatory
9As discussed in Anderson and van Wincoop (2001), liberalization of trade costs that generate rents for
home agents have smaller welfare impacts than liberalization of "real" trade costs that absorb resources.
15
or most-favored-nation (MFN) basis. This would raise welfare, as measured by equivalent
variation in the representative agent's real income, by about 1.2 percent. The model also
simulates impacts on the real wage and return on capital. While both factors would gain, the
benefits would be larger for capital (a 1.32 percent increase in price), with the real wage
increasing by less than one percent. In terms of factor adjustment, 0.8 percent of the labor force
and one percent of capital would turn over industry of employment.
The investment liberalization (mode 3) scenario shown in column 2 of Table 5 is the
same as that discussed above (column 2 of Table 4). Finally, the aggregate impact of liberalizing
both investment barriers and border barriers (modes one and three) is slightly more than additive
as shown in column 3, raising welfare by 5.3 percent. Note that roughly 75.5 percent of
estimated welfare gains may be attributed to investment liberalization, while 23.0 percent are due
to border liberalization. This leaves a small positive residual gain of 1.5 percent that stems from
the fact that both types of barriers together interact to generate a larger income loss than they
would separately. It is interesting that this interaction process affects labor and capital
differently. The individual liberalization impacts on the real wage sum to less than the joint
impact of full liberalization, suggesting that the barriers interact to restrain wages. The opposite
is true for the real price of capital. Finally, note in the bottom panel that any policy reform
expands the share of services compared to the initial benchmark. However, mode 1 liberalization
favors manufacturing and mining over full liberalization in mode 1 and mode 3, which favors
agriculture and services. Indeed, full services liberalization would increase the services share of
GDP from 40.7 percent to 43.6 percent, a large shift in relative output.
It is possible also to consider the gains from liberalizing individual service sectors, as
reported in Table 6.10 For this purpose we compute the impacts of liberalizing both mode 1 and
mode 3 delivery options in six of the 11 tradable service sectors. About 41 percent of the welfare
10Note that sector-level reforms are assumed to occur in isolation while full liberalization entails the
simultaneous liberalization of all modeled service sectors. The aggregate impact does not equal the sum of
16
gains of full liberalization may be attributed to reforms in financial and transportation sectors.
The impact of liberalization in business services, distribution, and communications are also
substantial. Note that these individual trade reforms are not neutral with respect to factor prices.
Opening up the construction sector would actually reduce the real wage moderately. Capital
income would gain significantly from liberalization of transportation, business services, and
finance.
The final set of scenarios compares liberalization of goods and services. Goods-trade
liberalization is modeled as a non-discriminatory and unilateral elimination of the commodity
tariffs given in Table 2. Results are shown in Table 7. Household welfare is estimated to
increase by 1.5 percent, in contrast to the 5.3 percent gain from full services liberalization. As
trade theory would predict, the gains are largely experienced by the abundant factor, labor, while
there is relatively little change in the price of other value added. The wage increases nearly 19
percent while returns to capital increase 3.5 percent. Factor turnover is also quite high at 10
percent for both workers and capital. There is a significant increase in the manufacturing share of
total output from 32.8 percent in the benchmark to 42.8 percent in the free goods-trade
environment. Agriculture declines substantially as a relative component of output, as does
services.
Liberalizing services barriers and goods tariffs simultaneously yields a potential gain in
welfare of 6.7 percent. These gains are less than the sum available under the isolated
liberalization packages, indicating that there is a somewhat offsetting interaction between the two
commitments. Gains from joint liberalization, however, are more evenly distributed across labor
and capital than they are in either individual reform. Thus, removal of goods tariffs strongly
favors labor while removal of services barriers favors capital. Both factors experience significant
real price increases with joint liberalization.
the sectoral impacts due to interactions between sectors with joint liberalization.
17
Interestingly, the structure of output with full liberalization of both goods and services is
closer to that with an isolated service liberalization than to one with solely goods tariff
elimination, as noted in the bottom panel. Thus, in an important sense, removing commodity
tariffs without services liberalization tends to "over-adjust" the economy toward manufacturing
and away from agriculture and services. Freeing up services moves the structure back toward the
fully efficient outcome in the final column. Indeed, a pure goods-trade liberalization results in a
much greater movement of labor and more dramatic changes in the composition of production.
6. CONCLUSIONS
This paper considers how services liberalization differs from that of goods liberalization
using an applied general equilibrium model of Tunisia's economy. Not surprisingly, goods-trade
liberalization reorients production towards manufacturing (especially in textile and electronics) in
line with Tunisia's benchmark comparative advantage. In contrast, the overall composition of
production with service liberalization remains fairly stable, with only slight increases in
manufacturing and service provision and a small decrease in agriculture and mining. The
distribution of gain under service liberalization are more evenly distributed across factors than
those under goods liberalization, where gains are strongly concentrated in the hands of workers
(the abundant factor). Fewer workers are required to change positions to accommodate service
liberalization, implying less impact on frictional unemployment. Thus, we might expect less
political resistance to services liberalization relative to goods liberalization.
Interestingly, combining goods and services liberalization appears to offer the best of
both worlds. The gains from jointly freeing up goods and services are nearly additive of the two
independent reforms. Yet the overall structure of the economy remains similar to that of the
benchmark, with relatively small changes in the employment location of workers. Services
liberalization therefore eases the adjustment costs involved in the liberalization of goods trade as
18
the expansion of economic activity would no longer be restrained by the lagging competitiveness
of Tunisia's service sector.
The potential welfare implications of services liberalization are clearly positive and
substantial. Even given modest assumptions about the current environment for trade in services,
welfare (measured as equivalent variation) and GDP are both estimated to increase more than
seven percent. These gains are more than three times the magnitude of the estimated gains from
goods-trade liberalization alone. Further, perhaps 75 percent of services liberalization gains are
to be achieved from the liberalization of foreign investment barriers that impede mode 3 delivery
of services. Granting the right of establishment to foreign firms stands to increase real household
income by four percent. In contrast, liberalization of cross-border trade in services (mode 1)
results in a roughly one percent gain in household income.
The uncertainty surrounding estimated price wedges and the allocation of those wedges
between rent and production inefficiency deserve further exploration. Improved estimates of
services barriers are critical for a more accurate determination of the magnitude of the potential
impacts of liberalization. It is important to note that cautious assumptions were made here about
the existing distortions and the potential competitive effects and efficiency improvements with
liberalization. It may be that a dramatic reform effort might bring even greater gains than those
reported here.
19
Figure 1 1Ffigure 1.FFigure 1
Domestic
OUTPUT CET
Export
CET
Leontief (linear)
EU MENA ROW
Value Added Intermediate Inputs
Leontief (linear)
CES ......... Composite Intermediate (i) ....
CES
Labor Capital
Domestic Import
CES
EU MENA ROW
UTILITY
CD
Sector (1) .......... Sector (i) .......... Sector (n)
CES
Domestic Import
CES
EU MENA ROW
20
APPENDIX: MODEL EQUATIONS AND NOTATION
A. Production
1. Value Added Function Vi = [aLiLi (i-1)/i + aKiKi (i-1)/i i/(i-1)
]
2. Imported Intermediates MiN = [rrimriN (i-1)/ i i/(i-1)
]
3. Composite Intermediate zji = [didji(j-1)/ j + mimji (j-1)/ j j/(j-1)
]
4. Final Goods Technology Yi = min[z1i/a1i,..,zni/ani,Vi/aVA]
5. Domestic & Foreign Sales Yi = [DiDi (i-1)/i + XiXi (i-1)/i i/(i-1)
]
6. Export Allocation Xi = [rriXri (ei-1)/ei ei/(ei-1)
]
7. Marginal Cost Condition (1+i)ciYi = j(1+vj)pjdji + jr(1+uj+trj)prj mrji m
+ (wKKi + wLL1i)
B. Utility
8. Utility Function U = iCi ; ibi = 1
bi
9. Domestic & Import Consumption Ci = [DiDiC (i-1)/ i + MiCMiC (i-1)/ i i/i-i
]
(applies also to Gi and Ii )
F
10. Import Allocation MiC = [rriMric (i-1)/ i i/i-1
]
(applies also to MiG and MiI )
F
C. Constraints and Balancing Items
11. Agent's Budget Constraint i~pi Ci = wKEK + wLiLi+ - i~pi Ii
C IF F
-ipiIi - rFKF - D + i viYi
I
12. Government Budget Constraint i~pi Gi = D +iVi~pi Vi + irtripri (MriC+MriI )
G C m F
13. Current Account Balance 0 = ri(1/e)(pri Mri - pri Xri - wL L + rFKF)
m x F F
14. Product Market Clearance Si = jaijYj + Gi + Ii + Ii + Ci
F I
15. Factor Market Clearance iKi =EK ; iLi =E1L
16. Zero Profits pi Di + rpri Xri = ciYi
x
17. Supply Value Balance ~pi Si = ~pi jaij(1+vi)Yj +
Z ~C
pi DiC+ ~pi DiI +
IF F ~pi
GDiG
+ ~pi Ii +r(1+ui+tri)pri (MriC + MriG+MriI )
IF I m F
21
D. Price Relationships and Identities
18. Components of Domestic Sales Di = DiC + DiI + Ii + DiG
F I
19. Components of Import Sales Mi = MiN + MiC + MiI + MiG
F
20. Domestic Price of Intermediate Imports pri = (1 + ui + tri)pri
N m
(holds also for imports for G)
21. Domestic Price of Imports for C pri = (1 + ui + tri)pri
C m
(holds also for imports for IF)
22. Consumer Price of Domestic Goods pi = (1 + vi)pi
C
(holds also for purchases for IF)
23. Capital-Market Equilibrium K1+ wK1 = ... = Kn + wKn (mobile capital sectors)
LIST OF VARIABLES
Li Domestic labor inputs, sector i (i=1,..,34)
Ki Capital (other value added) inputs, both mobile and immobile
Vi Value added
Mi Total imports
Mri Imports from region r (r = EU, MENA, ROW)
MiN Imports of commodity i for intermediate use
mriN Imports for intermediate use from region r (r = EU, MENA, ROW)
zji Composite intermediate input of j into i (j=1,...,34)
dji, mji Intermediate usages of domestic and imported goods
Yi Output of good i
Di, Xi Output for domestic sales and exports
DiC, DiG, DiI F Domestic sales: private and public consumption, capital formation
Xri Exports of good i to region r
ci Index of marginal cost of production
pi Domestic producer price index
~Z ~C ~IF ~pi
pi ,pi , pi , G Domestic price indexes (home and imported prices)
wK, wL Factor price indexes
U Utility
~pi Composite price index for total domestic supply
Ci, Gi Private and public consumption
Ii , Ii
F I Fixed capital formation and inventory investment
MiC, MiG Imports for private and public consumption
22
MiI F Imports for fixed capital formation
MriC, MriG Imports for private and public consumption from region r
MriIF Imports for fixed capital formation from region r
KF Net payments on foreign capital holdings
e Real exchange rate (price index for foreign exchange)
B Current-account balance
D Government budget deficit (held fixed)
Si Supply on domestic market (Di + Mi)
priN Domestic price index for intermediate imports
pri , pri
C G Domestic price indexes for imports of private and public consumption
priI
F Domestic price index for imports for gross capital formation
pi , piI
C F Price index for private consumption/fixed capital of domestic goods
pri Producer price index for goods exported to region r
LIST OF PARAMETERS
i Substitution elasticity between capital and labor
a Substitution elasticity between intermediates and value added
i Armington elasticity on imports between regions
j Substitution elasticity between domestic and imported intermediates
i Transformation elasticity between domestic and exported output
ei Transformation elasticity on exports between regions
i Substitution elasticity between domestic and imported consumption
tri Tariff rate on imports from region r (tri= 0 for service sectors)
ui Resource-using services border barriers (ui=0 for non-service sectors)
vi Service rents on output (vi=0 for non-service sectors)
i Service resource-using barriers on output (i=0 for non-service sectors)
EK , E1L Endowment of capital and labor
prim Price of imports from region r
prix Price of exports in region r
rF Price of foreign capital payments
23
References
Anderson, James E. and Eric van wincoop, 2001, "Borders, Trade, and Welfare," forthcoming in
Susan Collins and Dani Rodrik, editors, Brookings Trade Forum 2001.
Bahlous, Mejda and Mustapha K. Nabli, 2000, "Financial Liberalization and Financing
Constraints on the Corporate Sector in Tunisia," Working Paper No 2005, Economic
Research Forum for the Arab Countries.
Brown, Drusilla, Alan Deardorff, Alan Fox, and Robert M. Stern, 1996, "Computational Analysis
of Goods and Services Liberalization in the Uruguay Round," in Will Martin and L. Alan
Winters, editors, The Uruguay Round and Developing Economies, Cambridge University
Press.
Brown, Drusilla K., and Robert M. Stern, 2001, "Measurement and Modeling of the Economic
Effects of Trade and Investment Barriers in Services," Review of International
Economics, 9: 262-86.
Dee, Philippa and Kevin Hanslow, 2001, "Multilateral Liberalization of Services Trade," in
Robert M. Stern, editor, Services in the International Economy, University of Michigan
Press, Ann Arbor.
Dee, Philippa, Alexis Hardin and Leanne Holmes, 2000, "Issues in the Application of CGE
Models to Services Trade Liberalization," in Christopher Findlay and Tony Warren,
editors, Impediments to Trade in Services: Measurement and Policy Implications,
Routledge, London and New York.
Francois, Joseph, 1999, "A Gravity Approach to Measuring Services Protection," Manuscript,
Erasmus University.
Francois, Joseph and Ian Wooton, 2001, "Market Structure, Trade Liberalization, and the GATS,"
European Journal of Political Economics 17: 389-402.
Goaied, Mohamed, (1999), "Cost-frontier Analysis of Tunisian Commercial Banking Sectors,"
manuscript.
Harrison, G.W., R. Jones, L. Kimbell Jr., and R. Wigle. 1993. "How Robust is Applied General
Equilibrium Modeling?" Journal of Policy Modeling 15: 99-115. NOT IN TEXT
Hertel, Thomas W., 2000, "Potential Gains from Reducing Trade Barriers in Manufacturing,
Services and Agriculture," in Multilateral Trade Negotiations: Issues for the Millenium
Round, St. Louis: Federal Reserve Bank of St. Louis.
Hoekman, Bernard, 1995, "Tentative First Steps: An Assessment of the Uruguay Round
Agreement on Services," World Bank Policy Research Working Paper 1455. Washington
DC.
Hoekman, Bernard, 2000, "The Next Round of Services Negotiations: Identifying Priorities and
Options," in Multilateral Trade Negotiations: Issues for the Millenium Round, St. Louis:
Federal Reserve Bank of St. Louis.
24
Hoekman, Bernard and Denise Eby Konan, 2000, "Rents, Red Tape, and Regionalism: Economic
Effects of Deeper Integration," in B. Hoekman and J. Zarrouk, editors, Catching Up with
the Competition: Trade Policy Challenges and Options for the Middle East and North
Africa, Ann Arbor: University of Michigan Press.
Institute National De La Statistique (INS), 1998, Les Comptes de la Nation, agregats et tableaux
d'ensemble 1993-1997, Tunis: INS Press.
Kalirajan, Kaleeswaran, Greg McGuire, Duc Nguyen-Hong, and Michael Schuele, 2000, "The
Price Impact of restrictions on Banking Services," in Christopher Findlay and Tony
Warren, editors, Impediments to Trade in Services: Measurement and Policy
Implications, London and New York: Routledge.
Karsenty, Guy, 2000, "Assessing Trade in Services by Mode of Supply," in: GATS 2000: New
Directions in Services Trade Liberalization, Pierre Sauve and Robert M. Stern, editors,
Washington DC: Brookings Institution Press.
Kehoe, Timothy J., 2002, "An Evaluation of the Performance of Applied General Equilibrium
Models of the Impact of NAFTA," Federal Reserve Bank of Minneapolis, Research
Department Staff Report.
Konan, Denise Eby and Keith E. Maskus, 1997, "A Computable General Equilibrium Analysis of
Egyptian Trade Liberalization Scenarios," in Ahmad Galal and Bernard Hoekman,
editors, Regional Partners, Global Markets: Limits and Possibilities of the Euro-
Mediterranean Agreements, London: Center for Economic Policy Research in Europe
(CEPR) and Washington DC: Brookings Institution Press. NOT IN TEXT
Konan, Denise Eby and Keith E. Maskus. 2000. "Joint Trade Liberalization and Tax Reform in
a Small Open Economy: The Case of Egypt," Journal of Development Economics 61:
365-92.
Lipsey, Robert, 2001, "The New Economy: Theory and Measurement," paper for 27th Annual
PAFTAD Conference: The New Economy: Challenges for East Asia and the Pacific,
Canberra, Australia.
Markusen, James, Thomas F. Rutherford and David Tarr, 1999, "Foreign Direct Investment in
Services and the Domestic Market for Expertise," World Bank Policy Research Working
Paper 2431, Washington DC: The World Bank.
Maskus, Keith E. and Denise Eby Konan. 1997. "Trade Liberalization in Egypt," Review of
Development Economics, 1:275-93.
Rodrik, Dani, 2001, "Trading in Illusions," Foreign Policy, March/April, 54-62.
Rutherford, T., E.E. Rutstrom, and David Tarr. 1995. "The Free Trade Agreement Between
Tunisia and the European Union," World Bank, manuscript.
Warren, Tony and Christopher Findlay, 2000, "Measuring Impediments to Trade in Services," in:
GATS 2000: New Directions in Services Trade Liberalization, Pierre Sauve and Robert
M. Stern, editors, Washington DC: Brookings Institution Press.
25
Vittas, Dimitri, 1995, "The Insurance Sector in Tunisia, Financial Sector Development
Department," World Bank Working Paper, March 1995.
World Bank, 2000, Tunisia: Social and Structural Review 2000: Integrating into the World
Economy and Sustaining Economic and Social Progress, World Bank, Washington, DC.
Zarrouk, Jamel, 2000, "Regulatory Regimes and Trade Costs," in Bernard Hoekman and Jamel
Zarrouk, Editors, Catching Up with the Competition: Trade Opportunities and
Challenges for Arab Countries, Ann Arbor: University of Michigan Press.
26
TABLE 1: SECTORAL OUTPUT AND FACTOR SHARES (%)
Household Intermediate
Production Imports Consumption Consumption Exports
AGGREGATE SECTORS (% of total)
Agriculture and Fishing 17.5 10.2 32.4 20.1 6.6
Manufacturing 30.0 63.2 29.7 51.3 55.3
Utilities, Mining, Petroleum 5.8 5.8 4.0 10.9 6.8
Services 46.7 20.8 33.8 17.7 31.2
SERVICE SECTORS (% of total)
Construction 8.2 0.0 0.3 0.4 0.0
Distribution/Commerce 6.9 0.0 0.0 0.0 0.0
Transportation 5.6 2.7 5.7 4.3 8.7
Communication 1.0 0.1 0.3 1.7 0.4
Hotel 1.5 0.0 3.9 0.1 0.0
Restaurant 4.1 0.0 10.9 0.0 0.0
Finance 2.5 0.2 0.1 4.8 0.3
Insurance 0.3 0.2 0.3 0.6 0.0
Business 1.4 2.1 0.1 2.5 2.5
Real Estate 2.6 0.0 5.0 1.3 0.0
Repair 1.3 0.0 1.1 1.8 0.0
Health and Education 2.0 0.0 4.9 0.2 0.0
Public 9.0 0.0 0.6 0.0 0.0
Other Services 0.2 0.0 0.6 0.0 0.0
Tourism -- 15.4 -- -- 19.3
Institute National de la Statistique, 1998, Les Comptes de la Nation Base 1983, agregats et tableaux d'ensemble 1993-
1997.
27
Table 2: Benchmark Trade Shares and Tariffs
Trade-Weighted
EU Trade Share (%) Import Tariff
Sectors Imports Exports EU Rest of World
Agriculture 38.7 68.7 13.5 13.0
Process Foods 55.3 71.9 17.6 18.5
Chemicals and Glass 48.8 24.0 21.1 23.6
Non-Ferreous Metals 57.7 70.4 15.3 21.2
Metalwork 67.8 58.8 15.3 17.5
Machinery 77.0 86.0 6.5 8.5
Automobiles & Trucks 87.6 40.8 6.3 10.8
Automobile parts 57.1 71.0 0.1 1.7
Electrical Parts 66.4 50.4 4.3 7.8
Electronics 66.4 50.4 4.3 7.8
Household Appliances 66.4 50.4 4.3 7.8
Chemicals 75.7 39.2 9.0 10.3
Clothing & Textiles 92.3 94.8 17.7 21.6
Leather 93.3 96.6 25.1 28.3
Wood 41.1 66.7 16.4 16.6
Paper 74.4 20.6 11.1 5.3
Plastics 72.9 28.0 14.5 18.7
Other Manufacturing 72.9 76.2 8.1 15.8
Mining 30.6 86.0 17.4 2.5
Petroleum 63.3 38.7 12.2 20.2
Services 70.0 76.0
Table 3: Barriers to Trade in Services (NTB ad valorem price equivalent %)
Mode 1 Mode 3
Cross-border trade Foreign Presence
Construction nt 3
Distribution nt 5
Transportation 50 3
Communications 200 30
Hotel nt 3
Restaurant nt 3
Finance 30 30
Insurance 50 50
Business, Insurance & Leasing 10 10
Real Estate 10 10
Repair nt 3
Health and Education nt nt
Public nt nt
Other Services nt nt
nt non-traded modes of supply
28
Table 4: Liberalization of Foreign Direct Investment in Services
Baseline Scenario
Rent wedge: 100% Rent wedge: 50% Rent wedge: 0%
Cost wedge: 0% Cost wedge: 50% Cost wedge: 100%
Macroeconomic Variables (% change)
Welfare, Household Income (EV) 0.33 4.00 7.68
Consumer price index (CPI) -7.09 -7.11 -7.13
Price of Labor 4.39 3.19 2.04
Price of Capital 6.55 6.99 7.43
Labor turnover 3.44 3.42 3.78
Capital Turnover 4.87 4.90 5.06
Production (share of GDP)
Agriculture (bench = 19.5 percent) 21.1 21.2 21.3
Manufacturing (32.8 percent) 28.5 28.7 28.9
Mining and Utilities (7.0 percent) 6.8 6.8 6.7
Services (40.7 percent) 43.6 43.3 43.1
Table 5: Baseline Services Liberalization Scenarios
Border Investment Full Service
Liberalization Liberalization Liberalization
Macroeconomic Variables (% change)
Welfare, Household Income (EV) 1.22 4.00 5.30
Consumer price index -1.02 -7.11 -8.04
Price of Labor 0.57 3.19 4.23
Price of Capital 1.32 6.99 8.23
Labor turnover 0.78 3.42 3.73
Capital Turnover 0.98 4.90 5.35
Production (share of GDP)
Agriculture (bench = 19.5 percent) 19.9 21.2 21.4
Manufacturing (32.8 percent) 31.7 28.7 28.2
Mining and Utilities (7.0 percent) 7.1 6.8 6.8
Services (40.7 percent) 41.3 43.3 43.6
29
Table 6: Baseline Service liberalization (Mode 1 and Mode 3), by sector
Business, All
Commun- Construc- Transport- Insurance, & Distrib- Service
ications tion ation Leasing ution Finance Sectors
Welfare (EV) 0.46 0.32 1.09 0.60 0.44 1.08 5.30
Price Labor 0.90 -0.13 0.62 0.66 1.23 0.60 4.23
Price Capital 0.46 0.10 1.44 1.69 0.54 2.29 8.23
Labor Turnover 0.35 0.15 1.03 1.34 0.68 1.84 3.73
Capital Turnover 0.40 0.11 1.23 1.89 0.89 2.62 5.35
Table 7: Comparing Goods and Services Liberalization (Baseline Case)
Goods Services Goods and
Liberalization Liberalization Services
(Eliminate tariff) (Mode 1 & 3) Liberalization
Macroeconomic Variables (% change)
Welfare, Household Income (EV) 1.52 5.30 6.67
Consumer price index -1.07 -8.04 -9.07
Price of Labor 18.93 4.23 17.67
Price of Capital 3.46 8.23 13.61
Labor turnover 9.83 3.73 3.40
Capital Turnover 10.38 5.35 5.89
Production (share of GDP)
Agriculture (bench = 19.5 percent) 15.3 21.4 19.1
Manufacturing (32.8 percent) 42.8 28.2 33.6
Mining and Utilities (7.0 percent) 5.2 6.8 5.6
Services (40.7 percent) 36.7 43.6 41.7
30